Exploring Google APIs 102: Cloud vs. non-GCP Google APIs

Exploring Google APIs 102:
Cloud APIs vs. non-GCP Google APIs
Wesley Chun - @wescpy
Principal, CyberWeb Consulting
Adjunct CS Faculty, Foothill College

Principal, CyberWeb Consulting
● Mission: help developers everywhere
be successful using Google Cloud and
other Google developer tools & APIs
● Focus: Python, Google Cloud (APIs,
serverless, AI/ML), Google Workspace;
Google cross-product use cases
● Services: training, technical talks,
speak globally; make videos, create
code samples, produce codelabs (free,
self-paced, hands-on tutorials),
publish blog posts
About the speaker
Previous experience / background
● Software Engineer & Developer Advocate
○ Google, Sun, HP, Cisco, EMC, Xilinx
○ Original Yahoo!Mail engineer/SWE
● Technical trainer, teacher, instructor
○ Teaching Math, Linux, Python since '83
○ Adjunct CS Faculty at local SV college
● Python community member
○ Popular Core Python series author
○ Python Software Foundation Fellow
● AB (Math/CS) & CMP (Music/Piano), UC
Berkeley and MSCS, UC Santa Barbara
● Adjunct Computer Science Faculty, Foothill
College (Silicon Valley)
Google APIs: why & agenda
● Build on knowledge from "Exploring Google APIs" talks
● Highlight use of Cloud vs. non-GCP Google APIs
● Key difference: the client library you use
○ Lower-level client libraries vs. product-level client libraries
● Many code samples illustrate Cloud & non-GCP Google API usage
● Awareness reduces friction/challenges from using multiple Google APIs
1
Google APIs
introduction
2
Using Google
APIs
4
Cloud APIs
5
Other Google
APIs
6
Mix-n-match
& inspiration
3
Workspace
(non-GCP) APIs
7
Wrap-up

01
Intro to Google APIs
Why are you here?

BUT
... wait, there’s more...

Most products/APIs have "Quickstarts"
● Get started in 5 minutes!
● Available in most languages
02
Using Google APIs
Getting started & the nuts-n-bolts

The first word on Security
Authentication ("authn") vs authorization ("authz")
● authn: you are who you say you are
○ login & password
○ handprint authentication
○ retina scan
● authz: okay, you are who you say you are, but can you haz data?
○ OAuth2 - mostly authz, but some authn
○ Mostly about 3rd-party access to data
○ Users must give YOUR code access to THEIR data
○ Most of the time when you see "auth", it refers to authz
○ With Google APIs: permission scopes or IAM permissions/roles
● Some refer to this as "consent" vs. "credentials…" which is which?
General steps
1. Go to Cloud Console
2. Login to Google/Gmail account
(Workspace domain may require admin approval)
3. Create project (per application)
4. Enable APIs to use
5. Enable billing (CC, Free Trial, etc.)
6. Download client library(ies)
7. Create & download credentials
8. Write code
9. Run code (may need to authorize)
Google APIs: how to use
Costs and pricing
● GCP: pay-per-use
● Google Workspace: subscription
● GCP Free Trial ($300/1Q, CC req'd)
● GCP "Always Free" tier
○ Most products have free tier
○ Daily or monthly quota
○ Must exceed to incur billing
● More on both programs at
cloud.google.com/free
*In your code
1. Import API client library
2. Create API client object
3. Use client to make API Calls

Cloud/GCP console
console.cloud.google.com
● Hub of all developer activity
● Applications == projects
○ New project for new apps
○ Projects have a billing acct
● Manage billing accounts
○ Financial instrument required
○ Personal or corporate credit cards,
Free Trial, and education grants
● Access GCP product settings
● Manage users & security
● Manage APIs in devconsole
Billing & budgeting (your favorite subjects)

Collaborating & sharing
● Sharing: great way to see student work or have teams work on one project
● IAM (Identity & Access Mgmt): owner & editor most useful access levels
cloud.google.com/iam/docs/understanding-roles
● View application statistics
● En-/disable Google APIs
● Obtain application credentials
Using Google APIs
goo.gl/RbyTFD
API manager aka Developers Console (devconsole)
console.developers.google.com

Three different credentials types
● Simple: API keys (to access public data)
○ Simplest form of authorization: an API key; tied to a project
○ Allows access to public data
○ Do not put in code, lose, or upload to GitHub! (can be restricted however)
○ Supported by: Google Maps, (some) YouTube, (some) GCP, etc.
● Authorized: OAuth client IDs (to access data owned by [human] user)
○ Provides additional layer of security via OAuth2 (RFC 6749)
○ Owner must grant permission for your app to access their data
○ Access granularity determined by requested permissions (user scopes)
○ Supported by: Google Workspace, (some) YouTube, (some) GCP, etc.
● Authorized: service accounts (to access data owned by an app/robot user)
○ Provides additional layer of security via OAuth2 or JWT (RFC 7519)
○ Project owning data grants permission implicitly; requires public-private key-pair
○ Access granularity determined by Cloud IAM permissions granted to service account key-pair
○ Supported by: GCP, (some) Google Workspace, etc.

Two different client library "styles"
● "Platform-level" client libraries (lower-level)
○ Supports multiple products as a "lowest-common denominator"
○ Manage API service endpoints (setup & use)
○ Manage authorization (API keys, OAuth client IDs, service accounts)
○ Google Workspace, Google Analytics, YouTube, Google Ads APIs, GCP, etc.
○ Install: developers.google.com/api-client-library
● "Product-level" client libraries (higher-level)
○ Custom client libraries made specifically for each product
○ Managing API service endpoints & security mostly taken care of
○ Only need to create a "client" to use API services
○ Install (Cloud/GCP & Firebase): cloud.google.com/apis/docs/cloud-client-libraries
○ Install (Maps): developers.google.com/places/web-service/client-library
● Some Google APIs families support both, e.g., Cloud

&
Google APIs client
libraries for many
languages; demos in
developers.google.com/api-
client-library
cloud.google.com/apis/docs
/cloud-client-libraries
SIMPLE
AUTHORIZED
Which do you choose?

from googleapiclient import discovery
# Can copy from DevConsole, or better yet, put into Secret
# Manager, encrypted/secure store/DB, creds svr, proxy, etc.
from settings import API_KEY
# API information, i.e., (API='language', VERSION='v1')
SERVICE = discovery.build(API, VERSION, developerKey=API_KEY)
Simple API access(lower-level, generic)
import googlemaps
# Can copy from DevConsole, or better yet, put into Secret
# Manager, encrypted/secure store/DB, creds svr, proxy, etc.
GMAPS = googlemaps.Client(key=API_KEY)
print('n** Geocode address:')
rsp = GMAPS.geocode('1600 Amphitheatre Pkwy 94043')
latlong = rsp[0]['geometry']['location']
print('tGeocode:', latlong['lat'], ',', latlong['lng'])
Simple API access(higher-level, specific)

Google OAuth2 process
● Goal: valid access token == 3rd-party API data access
● How OAuth2 works (in general)
○ Step 1: Create OAuth2 credentials in DevConsole
○ Step 2: Send credentials to get access & refresh tokens
○ Step 3: Use access token to make authorized API calls
○ Step 4: Access tokens expire; use refresh to get new one
● developers.google.com/identity/protocols/OAuth2
● Other APIs will be similar with some differences
(User-)authorized API access(lower-level, older, generic)
OAuth boilerplate
goo.gl/KMfbeK
from httplib2 import Http
from oauth2client import file, client, tools
SCOPES = ... # at least one (string or array of strings)
# 'storage.json' - where to store OAuth2 tokens from API
# 'client_secret.json' - OAuth2 client ID & secret (download from DevConsole)
store = file.Storage('storage.json')
creds = store.get()
if not creds or creds.invalid:
flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)
creds = tools.run_flow(flow, store)
# create API service endpoint; for example: API='sheets', VERSION='v4'
SERVICE = discovery.build(API, VERSION, http=creds.authorize(Http()))

(User-)authorized API access(lower-level, newer, generic)
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
from google.oauth2 import credentials
# 'storage.json' - where to store OAuth2 tokens from API
# 'client_secret.json' - OAuth2 client ID & secret (download from DevConsole)
TOKENS = 'storage.json' # OAuth2 token storage
if os.path.exists(TOKENS):
creds = credentials.Credentials.from_authorized_user_file(TOKENS)
if not (creds and creds.valid):
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file('client_secret.json', SCOPES)
creds = flow.run_local_server()
with open(TOKENS, 'w') as token:
token.write(creds.to_json())
Service account access(lower-level, scopes, older, generic)
from oauth2client import service_account
# 'svc_acct.json' - OAuth2 service acct creds (download from DevConsole)
creds = service_account.ServiceAccountCredentials.from_json_keyfile_name(
'svc_acct.json', SCOPES)

Service account access(lower-level, svc acct, older, generic)
from oauth2client import client
. . .
# Creds file or (better) use Application Default Credentials (ADC)
# see cloud.google.com/docs/authentication/application-default-credentials
creds = client.GoogleCredentials.get_application_default()
SERVICE = discovery.build(API, VERSION, credentials=creds)
import google.auth
. . .
# Creds file or (better) use Application Default Credentials (ADC)
# see cloud.google.com/docs/authentication/application-default-credentials
creds, _proj_id = google.auth.default()
SERVICE = discovery.build(API, VERSION, credentials=creds)
Service account access(lower-level, svc acct, newer, generic)

from google.cloud import storage
# Implicit ADC usage (no security code visible!)
GCS = storage.Client() # uses ADC (app default creds)
blob = GCS.bucket(bucket).blob(FILENAME) # destination file
print('n** Uploading to %r' % BUCKET)
blob.upload_from_filename(FILENAME) # origin file
Service account access(higher-level, svc acct, newer, specific)
OAuth2 or
API key
HTTP-based REST APIs 1
HTTP
2
Google APIs request-response workflow
● Application makes request
● Request received by service
● Process data, return response
● Results sent to application
(typical client-server model)

03
Google Workspace
(formerly G Suite) APIs
Examples of non-Cloud Google APIs
Google Workspace
Top-level documentation and comprehensive developers
overview video at developers.google.com/gsuite
(formerly G Suite and Google Apps)
APIs

List (first 100) files/folders in Drive (older, OAuth2)
from __future__ import print_function
SCOPES = 'https://www.googleapis.com/auth/drive.metadata.readonly'
creds = store.get()
flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)
DRIVE = discovery.build('drive', 'v3', http=creds.authorize(Http()))
files = DRIVE.files().list().execute().get('files', [])
for f in files:
print(f['name'], f['mimeType'])
Listing your ﬁles
goo.gl/ZIgf8k
List (first 100) files/folders in Drive (newer, OAuth2)
import os.path
import pickle
from google.auth.transport.requests import Request
from google_auth_oauthlib.flow import InstalledAppFlow
creds = None
SCOPES = 'https://www.googleapis.com/auth/drive.metadata.readonly'
TOKENS = 'token.p' # where to store access & refresh tokens
if os.path.exists(TOKENS):
with open(TOKENS, 'rb') as token:
creds = pickle.load(token)
if not (creds and creds.valid):
if creds and creds.expired and creds.refresh_token:
creds.refresh(Request())
else:
flow = InstalledAppFlow.from_client_secrets_file('client_secret.json', SCOPES)
creds = flow.run_local_server()
with open(TOKENS, 'wb') as token:
pickle.dump(creds, token)
DRIVE = discovery.build('drive', 'v3', credentials=creds)
files = DRIVE.files().list().execute().get('files', [])
for f in files:
developers.google.com/drive/api/v3/quickstart/python

List (first 100) files/folders in Drive (newer, svc acct)
import google.auth
creds, _proj_id = google.auth.default() # ADC; shared w/SA
dr_client = discovery.build('drive', 'v4', credentials=creds)
files = dr_client.files().list().execute().get('files', [])
for f in files: # fields returned: mimeType, kind, id, name
Automate photo albums
OR

Try our Node.js customized reporting tool codelab:
g.co/codelabs/sheets
Why use the Sheets API?
data visualization
customized reports
Sheets as a data source
Migrate SQL data to a Sheet
# read SQL data then create new spreadsheet & add rows into it
FIELDS = ('ID', 'Customer Name', 'Product Code',
'Units Ordered', 'Unit Price', 'Status')
cxn = sqlite3.connect('db.sqlite')
cur = cxn.cursor()
rows = cur.execute('SELECT * FROM orders').fetchall()
cxn.close()
rows.insert(0, FIELDS)
DATA = {'properties': {'title': 'Customer orders'}}
SHEET_ID = SHEETS.spreadsheets().create(body=DATA,
fields='spreadsheetId').execute().get('spreadsheetId')
SHEETS.spreadsheets().values().update(spreadsheetId=SHEET_ID, range='A1',
body={'values': rows}, valueInputOption='RAW').execute()
Migrate SQL data
to Sheets
goo.gl/N1RPwC

Try our Node.js BigQuery GitHub license analyzer codelab:
g.co/codelabs/slides
Why use the Slides API?
data visualization
presentable reports
Try our Node.js Markdown-to-Google-Slides generator:
github.com/gsuitedevs/md2googleslides
Why use the Slides API?
customized presentations

Replace text & images from template deck
requests = [
# (global) search-and-replace text
{'replaceAllText': {
'findText': '{{TITLE}}',
'replaceText': 'Hello World!',
}},
# replace text-based image placeholders (global)
{'replaceAllShapesWithImage': {
'imageUrl': IMG_URL, # link to product logo
'replaceMethod': 'CENTER_INSIDE',
'containsText': {'text': '{{LOGO}}'},
}},
]
SLIDES.presentations().batchUpdate(body={'requests': requests},
presentationId=DECK_ID, fields='').execute()
Replacing text
and images
goo.gl/o6EFwk
Display Gmail threads (& # of messages)
# get all "busy" mail threads & display (non-blank) Subject lines
threads = GMAIL.users().threads().list(userId='me',
fields='threads').execute().get('threads', [])
for thread in threads:
tdata = GMAIL.users().threads().get(userId='me', id=thread['id'],
format='metadata', metadataHeaders=['subject'],
fields='messages/payload/headers(name,value)').execute()
if 'messages' not in tdata:
continue
if len(tdata['messages']) > 10:
msg = tdata['messages'][0]['payload']
subject = ''
for header in msg['headers']:
if header['name'] == 'Subject':
subject = header['value']
break
if subject:
print('%2d message(s) in thread: %s' % (
len(tdata['messages']), subject))
Gmail threads
goo.gl/pFYUQ2

Creating events in Calendar
# define event data, then create event
TIMEZONE = 'America/Los_Angeles'
EVENT = {
'summary': 'Dinner with friends',
'start': {'dateTime': '2017-06-14T19:00:00', 'timeZone': TIMEZONE},
'end': {'dateTime': '2017-06-14T22:00:00', 'timeZone': TIMEZONE},
'attendees': [
{'email': 'friend1@example.com'},
{'email': 'friend2@example.com'},
],
}
GCAL.events().insert(calendarId='primary', body=EVENT,
sendNotifications=True, fields='').execute()
Modifying and
recurring events
goo.gl/J2XkXc
Creating events
goo.gl/KuYMiq
+
Mail merge
=
Mail merge
goo.gle/2KrPNeG

Mail merge (get data from Sheets)
TMPL_ID = 'YOUR_DOCS_TEMPLATE'
SHEETS_ID = 'YOUR_DATA_SPREADSHEET'
SCOPES = (
'https://www.googleapis.com/auth/drive',
'https://www.googleapis.com/auth/documents',
'https://www.googleapis.com/auth/spreadsheets',
)
HTTP = creds.authorize(Http()) # ↙↙↙ how to access multiple APIs
DRIVE = discovery.build('drive', 'v3', http=HTTP)
DOCS = discovery.build('docs', 'v1', http=HTTP)
SHEETS = discovery.build('sheets', 'v4', http=HTTP)
# get data from spreadsheet, copy & merge template for each row
rows = SHEETS.spreadsheets().values().get(range='Sheet1',
spreadsheetId=SHEETS_ID).execute().get('values')[1:]
for row in rows:
DOCS_ID = DRIVE.files().copy(body={'name': 'Merged form letter'},
fileId=TMPL_ID, fields='id').execute().get('id')
Mail merge (template search & replace)
requests = [
# (global) search-and-replace text
{'replaceAllText': {
'containsText': {'text': '{{NAME}}'},
'replaceText': row['name'],
}},
]
DOCS.documents().batchUpdate(body={'requests': requests},
documentId=DOC_ID, fields='').execute()

04
Google Cloud APIs
Can use either Cloud and/or
lower-level client libraries

Storage: listing buckets
GCS = discovery.build('storage', 'v1')
BUCKET = YOUR_BUCKET
# send bucket name & return fields to API, display results
print('n** Objects in bucket %r...' % BUCKET)
FIELDS = 'items(name,size)'
files = GCS.objects().list(bucket=BUCKET, fields=FIELDS
).execute().get('items') or [{'name': '(none)', 'size': 'NaN'}]
for f in files:
print(' %s (%s)' % (f['name'], f['size']))
Storage: listing buckets
from google.cloud import storage
GCS = storage.Client()
BUCKET = YOUR_BUCKET
# send bucket name & return fields to API, display results
print('n** Objects in bucket %r...' % BUCKET)
for f in GCS.list_blobs(BUCKET):
print(' %s (%s)' % (f['name'], f['size']))

Firestore (Datastore): object create & query
from datetime import datetime
from google.cloud import datastore
DATASTORE = datastore.Client() # create Cloud Datastore client
def store_visit(remote_addr, user_agent):
'create new Visit entity in Datastore'
entity = datastore.Entity(key=DATASTORE.key('visit'))
entity.update({'timestamp': datetime.now(),
'visitor': '{}: {}'.format(remote_addr, user_agent)})
DATASTORE.put(entity)
def fetch_visits(limit):
'get most recent Visits'
query = DATASTORE.query(kind='visit')
query.order = ['-timestamp']
return query.fetch(limit=limit)
const {DatastoreClient} = require('@google-cloud/datastore);
const DATASTORE = new DatastoreClient();
// create new Visit entity in Datastore
async function storeVisit(remote_addr, user_agent) {
const entity = {
key: DATASTORE.key(['Visit']),
data: {
visitor: `${remote_addr}: ${user_agent}`,
timestamp: new Date()
}
};
await DATASTORE.save(entity);
// get most recent Visits
async function fetchVisits(limit) {
const query = DATASTORE.createQuery('Visit')
.order('timestamp', {descending: true}).limit(limit);
const [results] = await DATASTORE.runQuery(query);
Firestore (Datastore): object create & query

BigQuery: querying Shakespeare words
TITLE = "The top 10 most common words in all of Shakespeare's works"
QUERY = '''
SELECT LOWER(word) AS word, sum(word_count) AS count
FROM [bigquery-public-data:samples.shakespeare]
GROUP BY word ORDER BY count DESC LIMIT 10
'''
BQ = discovery.build('bigquery', 'v2', http=creds.authorize(Http()))
rsp = BQ.query(body={'query': QUERY}, projectId=PROJ_ID).execute()
print('n*** Results for %r:n' % TITLE)
for col in rsp['schema']['fields']: # HEADERS
print(col['name'].upper(), end='t')
print()
for row in rsp['rows']: # DATA
for col in row['f']:
print(col['v'], end='t')
print()
BigQuery: querying Shakespeare words
from google.cloud import bigquery
TITLE = "The most common words in all of Shakespeare's works"
QUERY = '''
SELECT LOWER(word) AS word, sum(word_count) AS count
FROM `bigquery-public-data.samples.shakespeare`
GROUP BY word ORDER BY count DESC LIMIT 10
'''
rsp = bigquery.Client().query(QUERY).result()
print('n*** Results for %r:n' % TITLE)
print('t'.join(col.name.upper() for col in rsp.schema)) # HEADERS
print('n'.join('t'.join(str(x) for x in row.values()) for row in rsp)) # DATA

Top 10 most common Shakespeare words
$ python bq_shake.py
*** Results for "The most common words in all of Shakespeare's works":
WORD COUNT
the 29801
and 27529
i 21029
to 20957
of 18514
a 15370
you 14010
my 12936
in 11722
that 11519
● BigQuery public data sets: cloud.google.com/bigquery/public-data
● BQ sandbox (1TB/mo free): cloud.google.com/bigquery/docs/sandbox (see blog post)
● Other public data sets: cloud.google.com/public-datasets (Google Cloud),
research.google/tools/datasets (Google Research), and Kaggle (kaggle.com)
● COVID-19 BigQuery data sets
○ How to use our data sets (see blog post)
○ JHU Coronavirus COVID-19 Global Cases data set
○ List of all COVID-19 data sets
● Cloud Life Sciences API: cloud.google.com/life-sciences (see blog post)
● Cloud Healthcare API: cloud.google.com/healthcare (see blog post)
BigQuery and public data sets

IMG = 'gs://cloud-samples-data/vision/using_curl/shanghai.jpeg'
body = {'requests': [{
'image': {'source': {'imageUri': IMG}},
'features': [{'type': 'LABEL_DETECTION'}],
}]}
VISION = discovery.build('vision', 'v1', developerKey=API_KEY)
labeling = VISION.images().annotate(body=body).execute().get('responses')
for labels in labeling:
if 'labelAnnotations' in labels:
print('** Labels detected (and confidence score):')
for label in labels['labelAnnotations']:
print(label['description'], '(%.2f%%)' % (label['score']*100.))
Vision: label annotation/object detection
from google.cloud import vision
image_uri = 'gs://cloud-samples-data/vision/using_curl/shanghai.jpeg'
client = vision.ImageAnnotatorClient()
image = vision.types.Image()
image.source.image_uri = image_uri
response = client.label_detection(image=image)
print('Labels (and confidence score):')
print('=' * 30)
for label in response.label_annotations:
print(label.description, '(%.2f%%)' % (label.score*100.))

$ python3 label-detect.py
Labels (and confidence score):
==============================
People (95.05%)
Street (89.12%)
Mode of transport (89.09%)
Transport (85.13%)
Vehicle (84.69%)
Snapshot (84.11%)
Urban area (80.29%)
Infrastructure (73.14%)
Road (72.74%)
Pedestrian (68.90%)
g.co/codelabs/vision-python
05
Other Google APIs
Use lower-level or product-level
client libraries (see documentation)

Other Google APIs & platforms
● Firebase (mobile development platform + RT DB; ML Kit)
○ firebase.google.com & firebase.google.com/docs/ml-kit
● Google Data Studio (data visualization, dashboards, etc.)
○ datastudio.google.com/overview
○ goo.gle/datastudio-course
● Actions on Google/Assistant/DialogFlow (voice apps)
○ developers.google.com/actions
● YouTube (Data, Analytics, and Livestreaming APIs)
○ developers.google.com/youtube
● Google Maps (Maps, Routes, and Places APIs)
○ developers.google.com/maps
● Flutter (native apps [Android, iOS, web] w/1 code base[!])
○ flutter.dev
Search YouTube for videos
QUERY = 'python -snake'
trim = lambda x, ct: ('%s%s' % (x[:ct],
'...' if len(x)>ct else '')).ljust(ct+3)
print('n** Searching for %r videos...' % QUERY)
YOUTUBE = discovery.build('youtube', 'v3', developerKey=API_KEY)
res = YOUTUBE.search().list(q=QUERY, type='video',
part='id,snippet').execute().get('items', [])
for item in res:
print('http://youtu.be/%st%s' % (
trim(item['id']['videoId'], 24),
trim(item['snippet']['title'], 48)))

Maps APIs geocoding & places queries
import googlemaps
GMAPS = googlemaps.Client(key=API_KEY)
print('n** Geocode address:')
rsp = GMAPS.geocode('1600 Amphitheatre Pkwy 94043')
latlong = rsp[0]['geometry']['location']
print('tGeocode:', latlong['lat'], ',', latlong['lng'])
print('n** Address lookup:')
rsp = GMAPS.reverse_geocode((37.4222934, -122.0841409))
print('tAddress:', rsp[0]['formatted_address'])
print('n** Place query:')
pl_id = GMAPS.find_place('Villa Tugendhat',
input_type='textquery')['candidates'][0]['place_id']
place = GMAPS.place(pl_id)['result']
print('tPlace:t', place['name'])
print('tAddress:t', place['formatted_address'])
print('tWebsite:t', place['website'])
print('tMaps URL:t', place['url'])
$ python3 maps-demo-pub.py
** Geocode address:
Geocode: 37.4222934 , -122.0841409
** Address lookup:
Address: 1600 Amphitheatre Pkwy, Mountain View, CA
94043, USA
** Place query:
Place: Villa Tugendhat
Address: Černopolní 45, 613 00 Brno, Czechia
Website: tugendhat.eu
Maps URL: maps.google.com/?cid=5889127146370224362
Google Maps APIs
● Directions API
● Distance Matrix API
● Elevation API
● Geocoding API
● Geolocation API
● Time Zone API
● Roads API
● Places API
● Maps Static API
Google Apps Script
Customized serverless JS runtime for automation, and extension
and integration with Google Workspace (formerly G Suite) and
other Google & external services

+JavaScript
-API “flavor”
+built-in
“flavor”
-OAuth2 (you)
!=
“Hello World!” in Apps Script

Sheets-bound “Hello World!”
Apps Script intro
goo.gl/1sXeuD
What can you do with this?

Accessing maps from
spreadsheets?!?
goo.gl/oAzBN9
This… with help from Google Maps & Gmail
function sendMap() {
var sheet = SpreadsheetApp.getActiveSheet();
var address = sheet.getRange("A2").getValue();
var map = Maps.newStaticMap().addMarker(address);
GmailApp.sendEmail('friend@example.com', 'Map',
'See below.', {attachments:[map]});
}
JS
g.co/codelabs/apps-script-intro

06
Mix-n-match &
inspiration
Use Cloud and lower-level
(LL) client libraries or just LL
Cloud image processing workflow
Archive and analyze Google Workspace
(formerly G Suite) images with GCP

Image: Gerd Altmann from Pixabay

Cloud
Vision
Google Workspace GCP
Cloud
Storage
Drive
Sheets
Archive
image
Categorize
image
Record
results

import argparse, base64, io, webbrowser
from googleapiclient import discovery, http
k_ize = lambda b: '%6.2fK' % (b/1000.) # bytes to kBs
FILE = 'YOUR_IMG_ON_DRIVE'
BUCKET = 'YOUR_BUCKET_NAME'
PARENT = '' # YOUR IMG FILE PREFIX
SHEET = 'YOUR_SHEET_ID'
TOP = 5 # TOP # of VISION LABELS TO SAVE
DEBUG = False
# process credentials for OAuth2 tokens
SCOPES = (
'https://www.googleapis.com/auth/drive.readonly',
'https://www.googleapis.com/auth/devstorage',
'https://www.googleapis.com/auth/cloud-vision',
)
creds = store.get()
flow = client.flow_from_clientsecrets(
'client_secret.json', SCOPES)
# create API service endpoints
HTTP = creds.authorize(Http())
GCS = discovery.build('storage', 'v1', http=HTTP)
VISION = discovery.build('vision', 'v1', http=HTTP)
import argparse, base64, io, webbrowser
from googleapiclient import discovery, http
from google.cloud import storage, vision
k_ize = lambda b: '%6.2fK' % (b/1000.) # bytes to kBs
FILE = 'YOUR_IMG_ON_DRIVE'
BUCKET = 'YOUR_BUCKET_NAME'
PARENT = '' # YOUR IMG FILE PREFIX
SHEET = 'YOUR_SHEET_ID'
TOP = 5 # TOP # of VISION LABELS TO SAVE
DEBUG = False
# process credentials for OAuth2 tokens
SCOPES = (
'https://www.googleapis.com/auth/drive.readonly',
'https://www.googleapis.com/auth/devstorage',
'https://www.googleapis.com/auth/cloud-vision',
)
creds = store.get()
flow = client.flow_from_clientsecrets(
'client_secret.json', SCOPES)
# create API service endpoints
HTTP = creds.authorize(Http())
GCS = storage.Client()
VISION = vision.ImageAnnotatorClient()

def drive_get_file(fname):
rsp = DRIVE.files().list(q="name='%s'" % fname).execute().get['files'][0]
fileId, fname, mtype = rsp['id'], rsp['name'], rsp['mimeType']
blob = DRIVE.files().get_media(fileId).execute()
return fname, mtype, rsp['modifiedTime'], blob
def gcs_blob_upload(fname, bucket, blob, mimetype):
body = {'name': fname, 'uploadType': 'multipart',
'contentType': mimetype}
return GCS.objects().insert(bucket, body, blob).execute()
def vision_label_img(img, top):
body = {'requests': [{'image': {'content': img}, 'features':
[{'type': 'LABEL_DETECTION', 'maxResults': top}]}]}
rsp = VISION.images().annotate(
body=body).execute().get['responses'][0]
return ', '.join('%s (%.2f%%)' % (label['description'],
label['score']*100.) for label in rsp['labelAnnotations'])
def sheet_append_row(sheet, row):
rsp = SHEETS.spreadsheets().values().append(
spreadsheetId=sheet, range='Sheet1',
body={'values': rows}).execute()
return rsp.get('updates').get('updatedCells')
def main(fname, bucket, sheet_id, top):
fname, mtype, ftime, data = drive_get_img(fname)
gcs_blob_upload(fname, bucket, data, mtype)
rsp = vision_label_img(data, top)
sheet_append_row(sheet_id, [fname, mtype,
ftime, len(data), rsp])
API method calls in Bold
Driver calls in Bold Italics
def drive_get_file(fname):
rsp = DRIVE.files().list(q="name='%s'" % fname).execute().get['files'][0]
fileId, fname, mtype = rsp['id'], rsp['name'], rsp['mimeType']
blob = DRIVE.files().get_media(fileId).execute()
return fname, mtype, rsp['modifiedTime'], blob
def gcs_blob_upload(fname, bucket, blob, mimetype):
blob = GCS.bucket(bucket).blob(fname)
blob.upload_from_string(media, mimetype)
return {'bucket': bucket, 'name': fname}
def vision_label_img(img, top):
image = vision.types.Image(content=img)
labels = VISION.label_detection(image=image,
max_results=top).label_annotations
return ', '.join('(%.2f%%) %s' % (
label.score*100., label.description) for label in labels)
def sheet_append_row(sheet, row):
rsp = SHEETS.spreadsheets().values().append(
spreadsheetId=sheet, range='Sheet1',
body={'values': rows}).execute()
return rsp.get('updates').get('updatedCells')
def main(fname, bucket, sheet_id, top):
fname, mtype, ftime, data = drive_get_img(fname)
gcs_blob_upload(fname, bucket, data, mtype)
rsp = vision_label_img(data, top)
sheet_append_row(sheet_id, [fname, mtype,
ftime, len(data), rsp])
API method calls in Bold
Driver calls in Bold Italics

● Project goal: Imagining an actual enterprise use case and solve it!
● Specific goals: free-up highly-utilized resource, archive data to
colder/cheaper storage, analyze images, generate report for mgmt
● Download image binary from Google Drive
● Upload object to Cloud Storage bucket
● Send payload for analysis by Cloud Vision
● Write back-up location & analysis results into Google Sheets
● Blog post: goo.gle/3nPxmlc (original post); Cloud X-post
● Codelab: free, online, self-paced, hands-on tutorial
● g.co/codelabs/drive-gcs-vision-sheets
● Application source code
● github.com/googlecodelabs/analyze_gsimg
App summary
07
Wrap-up
Summary & resources

Session Summary
● Google provides more than just apps
○ More than search, YouTube, Android, Chrome, and Gmail/Docs
○ Much Google techology available to developers via APIs
● Google Cloud vs. non-Cloud Google APIs
○ Alas, developer experience differs between product families
○ Some products have higher-level product client libraries
○ Others require use of lower-level client libraries
■ Lower-level may be useful as lowest common denominator
● Inconsistency due to various reasons: budget, timeframe, priorities, etc.
● Interesting possibilities using multiple Google product APIs
Client libraries & credentials review
● Two different client library types
○ Platform-level client libraries (lower-level)
■ Multiple product groups as a "lowest-common denominator"
■ Install: developers.google.com/api-client-library
○ Product-level client libraries (higher-level)
■ Custom client libraries made specifically for 1 product or product group
■ Found on product or product group page(s)
● Three different credentials types
○ Simple: API keys (access public data)
■ Simplest form of authorization: an API key; tied to a project
○ Authorized: OAuth client IDs (access data owned by [human] user)
■ Provides additional layer of security via OAuth2 (RFC 6749)
○ Authorized: service accounts (access data owned by an app/robot user)
■ Provides additional layer of security via OAuth2 or JWT (RFC 7519)

● Documentation (most APIs have "Quickstarts")
○ Google Cloud: cloud.google.com/{docs,appengine,functions,run,vision,automl,translate,language,
speech,texttospeech,video-intelligence,firestore,bigquery,compute,storage,gpu,tpu}
○ Google Workspace:
developers.google.com/{gsuite,drive,calendar,gmail,docs,sheets,slides,apps-script}
● Google codelabs (self-paced, hands-on tutorials): need a Google account, always free
○ GWS: g.co/codelabs/gsuite-apis-intro (Drive), g.co/codelabs/sheets (Sheets), g.co/codelabs/slides (Slides)
○ GCP: gcplab.me or g.co/codelabs/cloud
● Cloud Skills Boost (codelabs by QwikLabs): don't need a Google acct; typically not free
○ cloudskillsboost.google or google.qwiklabs.com
● Videos: youtube.com/GoogleCloudPlatform (Cloud) and goo.gl/JpBQ40 (Workspace)
● Code samples: github.com/GoogleCloudPlatform (Cloud) and github.com/googleworkspace (Workspace)
● Cloud Free Trial (new users) and Always Free (daily/monthly tier) programs: cloud.google.com/free
● Know AWS/Azure? Compare with Google Cloud products at cloud.google.com/docs/compare/aws
● Language support: cloud.google.com/{python,java,nodejs,go,php,ruby,dotnet}
Additional resources
"Free" … what is and what isn't?
● GCP free programs
○ Free Trial
■ $300USD credit good for 3 months
■ Billing/credit card required; expires
○ "Always Free" tier
■ Some GCP products free up to usage limits
■ Independent of Free Trial & education grants
■ Billing/credit card required; no expiration (subject to change)
○ cloud.google.com/free
● Google Workspace APIs/platforms
○ "Free" up to usage limits
○ Covered by monthly subscription fee
○ Pay-for or free Gmail consumer accts
○ Billing required; no expiration
● GCP education (teaching & research) grants
○ (Your) credit card NOT required; expires
○ Meant to provide initial "free" usage for coursework or research
○ cloud.google.com/edu
$$ FREE $$

Bring me to your
organization ... it's my job to
help you!
● "TOI" tech talks
● Half- or full-day seminars
● Hands-on "codelab" workshops
● Multi-day training courses
● Migration strategy & planning
● cyberwebconsulting.com
Thank you! Questions?
Wesley Chun
@wescpy
cyberwebconsulting.com
Progress bars: goo.gl/69EJVw

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